Database and method for evaluating data therefrom

a data and data technology, applied in the field of data bases for storing data, can solve the problems of not providing an efficient means for allowing large amounts of contiguous data to be accessed and/or evaluated, and not being able to meet the needs of small clients, so as to achieve the effect of maintaining safety, enhancing damping, and efficient monitoring of different phenomena

Active Publication Date: 2016-07-28
FAKEIH ADNAN
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0087]Information in data servers must be protected from network borne attacks [H. Li and S. Lee, Mining frequent itemsets over data streams using efficient window sliding techniques, Expert Systems with Applications, Volume 36, Issue 2, Part 1, March 2009, Pages 1466-1477], [W. Wang, X. Guan and X. Zhang, Processing of massive audit streams for real-time anomaly intrusion detection, Computer Communications, Volume 31, Issue 1 (January 2008), Pages: 58-72]. The two basic approaches consist of signature based detection where malicious behavior is detected by matching against previously stored prototypical attacks and anomaly detection where the profile of a normal user is maintained and an attempt is made to identify unacceptable deviation as a possible attack. The signature based approach can be adapted to make use of the invention's distance measurement mechanism where distances to a predefined set of signatures are recorded in real-time. The unique advantage of the invention is that not only distances to the complete signature are obtainable, but also distances to signature subsets are possible. This allows for quick experimentation and testing capabilities that do not require time consuming distance re-computation. Anomaly detection also benefits from the ability to perform calculations over data subsets. This is especially suitable for automated calibration approaches where multiple time periods can be measured simultaneously with no additional computation and vastly reduced bandwidth costs compared to a conventional approach.
[0089]Monitoring technology is used to track the performance of mass damping systems for tall concrete structures to enhance their damping and maintain their safety [J. M. W. Brownjohn, E. P. Carden, C. R. Goddard and G. Oudin, Real time performance monitoring of tuned mass damper system for a 183 m reinforced concrete chimney. Journal of Wind Engineering and Industrial Aerodynamics Vol. 8, No. 3, March 2010, pp. 169-179]. Accelerometers are connected to the structure and remotely monitored to provide real-time information to determine whether the structures displacement exceeds critical thresholds. A large-scale application of this monitoring technology over hundreds or even thousands of structures would require a unified data management system such as the invention in order to allow all users to perform their required monitoring tasks simultaneously. With the compute-once, use-by-many approach, it is possible to efficiently have many automated systems monitoring different phenomena simultaneously through the use of different sized windows and data combinations. In addition, the low bandwidth requirement resulting from the cumulative data storage structure means that the monitoring sites can be remotely located with little overhead communications cost.
[0091]The goal is to optimize the drilling process to minimize cost while maintaining operational safety standards. This is done by continuously assessing the drilling process throughout the operation such that the overall rate of penetration is maximized based on cumulative footage drilled. The basic decision that must be made is to compromise between maximizing the utilization of the drill head and minimizing project down time due to a damaged drill head and the associated lead time to replace and order new parts. This is performed by continuously analyzing several variables such as weight on bit and rotary speed, applying such data to mathematical models and making a decision as late as possible to maximize bit head usage while not endangering progress of the drilling project. An advantage of a solution based on the invention is that time windows can be customized at any time with a negligible computational penalty. This is important when drilling through different geological formations, varying the drilling speed or even real-time calibration of models as work progresses and ensures the ability to perform comprehensive analysis regardless of the initial strategy. This also allows for evaluating several different models simultaneously using the same initial data. In addition, the low bandwidth requirement is an important feature especially when drilling in harsh remote areas where it is difficult to locate analysts and acquiring large bandwidth communication channels is often cost prohibitive.Scientific Data Analysis
[0093]Early warning devices can provide a short warning before the arrival of major tremors based on the different propagation speeds of the various vibrations produced. This application is distinguished by large amounts of continuous data that need near instantaneous processing in order to be of value. Measurement centers can also make use of readings from neighboring centers in their effort to increase the detection time before an earthquake. Due to the large amount of data generated by each measurement device, this is prohibitively expensive for all but the largest centers. However, with the use of the invention as the data storage backbone, hundreds or even thousands of neighboring centers can share data making use of the low bandwidth requirement of the invention. In addition, the negligible calculation overhead for different sliding window sizes means that multiple levels of detection can be simultaneously performed in order to detect different size anomalies. This is important for experimentation since a large number of potential models can be simultaneously machine tested and potentially applied.
[0095]In-situ environmental sensors are physically located in the environment they are monitoring and their time-series data is transmitted continuously to a single data repository [D. J. Hill and B. S. Minsker, Anomaly detection in streaming environmental sensor data: A data-driven modeling approach, Environmental Modelling &Software, Volume 25, Issue 9, September 2010, Pages 1014-1022]. There is a need for automated data quality assurance and control to detect and identify anomalous data that deviates significantly from historical patterns. Such anomaly detection can also be used in the field of adaptive monitoring where anomalous data indicates phenomena that may require further investigation. The invention can be used as the main data depository where the customizable sliding windows mechanism can be used to perform simultaneous data assurance tests, thereby adding an additional layer of sophistication for quality monitoring. In addition, the same mechanism can be used to simultaneously detect multiple abnormal phenomena or allow for straight forward changes in detection strategy with a no additional computational cost. An added advantage is the ability to serve other remote users with their data requests with only a minimal communications investment due to the low bandwidth data transmission mechanism.DETAILED DESCRIPTION
[0096]The following explanation and examples 1-8 demonstrate how a database according to the first aspect of the invention may be constructed and used to store data and provide information in response to user queries.

Problems solved by technology

While these databases are well-suited to performing traditional transaction-oriented operations, they do not provide an efficient means for allowing large amounts of contiguous data to be accessed and / or evaluated, other than standard querying methods.
However, at present this is not possible with smaller clients due to costs associated with the large bandwidth and computational requirement needed for delivering the complete market feed.

Method used

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  • Database and method for evaluating data therefrom
  • Database and method for evaluating data therefrom
  • Database and method for evaluating data therefrom

Examples

Experimental program
Comparison scheme
Effect test

example 1

Data Storage

[0110]Taking the database of the first embodiment of first aspect of the invention, in which a cumulative value of the y variable is stored, the costs of building the database are set out below (compared to a comparative example for a conventional database):

[0111]Cost of adding a new record=computational cost of adding new record to sum of all previous records+storage cost for storing new cumulative record.

[0112]For conventional database, cost of adding a new record=storage cost for storing one more record (no computation cost)

[0113]The storage cost is the cost of sending the record to the network memory (including the use of network bandwidth).

[0114]The computational cost is the cost of the mathematical manipulation into the desired format.

[0115]Therefore, data storage in the first embodiment of the present invention has associated with it the additional computational cost (relative to the comparative example of a conventional database) of adding the new record to the s...

example 2

Data Manipulation

[0116]In this example, the mean average of a series of data records is calculated from the database of the first embodiment of the first aspect of the invention.

[0117]This requires the steps of:[0118]1. retrieving data records from the start and end of the series (retrieval cost=two fetch operations)[0119]2. subtracting start record value from end record value (computational cost=one subtraction operation)[0120]3. performing division by size of data (computation cost=one division operation)

[0121]In a conventional database, this process would require the steps of:[0122]1. retrieving all data records in the series of interest (retrieval cost=n fetch operations)[0123]2. performing summation over all retrieved records (computation cost=(n−1) addition operations)[0124]3. performing division by size of data (computational cost=one division operation)

[0125]Therefore, the database of the first embodiment of first aspect of the present invention has significantly lower retri...

example 3

Calculation of the Volume Weighted Average Price

[0126]The volume weighted average price (vwap) of a stock is obtained by dividing the total transacted money value by the total transacted volume. The money value of a transaction is the volume of the transaction multiplied by the price.

[0127]In a database according to a second embodiment of the first aspect of the present invention, the cumulative volume and the money value (the multiple of volume and price) are stored as a function of time. In this case, the vwap may be calculated by following the steps of:[0128]1. retrieving money value records from the start and end of the series of interest (retrieval cost=two fetch operations)[0129]2. subtracting start record from end record (computational cost=one subtraction operation)[0130]3. retrieving volume records from the start and end of the series of interest (retrieval cost=two fetch operations)[0131]4. subtracting start record from end record (computational cost=one subtraction operat...

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Abstract

A computer system for calculating a quantity from a set of input values. The computer system comprises a database that is configured to store a sequence of first input values xn wherein n=1, 2, . . . i, wherein for any value of n, xn lies between xn+1 and xn−1 in the sequence. Each value of x has associated with it a second input value yn, a conversion value pn that is calculated from yn according to a conversion algorithm, and an output value zn, wherein zn=zn−1+pn. The database is configured to store the plurality of output values zn.

Description

FIELD OF THE INVENTION[0001]The present invention relates to databases for storing data, and in particular to computer-implemented methods of constructing a database, storing data in the database, and / or methods of manipulating data stored in the database.BACKGROUND OF THE INVENTION[0002]A database is a structure for storing and relating data within e.g., a computer system. Different database architectures exist depending on the intended usage. The primary use for general purpose databases is to manage and facilitate data entry and retrieval in relation to the relevant application. A recent trend has been the emergence of specialized database architectures optimized to work with specific application domains.[0003]Complex event processing (CEP) is a technology for low-latency filtering, correlating, aggregating, and / or computing on real-world event data. Such data is usually generated at high frequencies and so needs to be saved in an appropriate database to allow it to be evaluated,...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): G06F17/30G06F17/11
CPCG06F17/30569G06F17/30386G06F17/11G06F17/30312G06F17/30536G06F16/258G06F16/21G06F16/22G06F16/24G06F16/2462G06F16/00
Inventor FAKEIH, ADNAN
Owner FAKEIH ADNAN
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